Genomic Risk Prediction for Breast Cancer in Older Women

Genomic risk prediction models for breast cancer (BC) have been predominantly developed with data from women aged 40-69 years. Prospective studies of older women aged ≥70 years have been limited. We assessed the effect of a 313-variant polygenic risk score (PRS) for BC in 6339 older women aged ≥70 years (mean age 75 years) enrolled into the ASPREE trial, a randomized double-blind placebo-controlled clinical trial investigating the effect of daily 100 mg aspirin on disability-free survival. We evaluated incident BC diagnoses over a median follow-up time of 4.7 years. A multivariable Cox regression model including conventional BC risk factors was applied to prospective data, and re-evaluated after adding the PRS. We also assessed the association of rare pathogenic variants (PVs) in BC susceptibility genes (BRCA1/BRCA2/PALB2/CHEK2/ATM). The PRS, as a continuous variable, was an independent predictor of incident BC (hazard ratio (HR) per standard deviation (SD) = 1.4, 95% confidence interval (CI) 1.3-1.6) and hormone receptor (ER/PR)-positive disease (HR = 1.5 (CI 1.2-1.9)). Women in the top quintile of the PRS distribution had over two-fold higher risk of BC than women in the lowest quintile (HR = 2.2 (CI 1.2-3.9)). The concordance index of the model without the PRS was 0.62 (95% CI 0.56-0.68), which improved after addition of the PRS to 0.65 (95% CI 0.59-0.71). Among 41 (0.6%) carriers of PVs in BC susceptibility genes, we observed no incident BC diagnoses. Our study demonstrates that a PRS predicts incident BC risk in women aged 70 years and older, suggesting potential clinical utility extends to this older age group.